Knowledge representation using multilevel hierarchical model in intelligent tutoring system
ACST'07 Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology
SIETTE: A Web-Based Tool for Adaptive Testing
International Journal of Artificial Intelligence in Education
A KST-BASED SYSTEM FOR STUDENT TUTORING
Applied Artificial Intelligence
Using Item Response Theory (IRT) to select hints in an ITS
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
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Language Studies are challenging for students at all levels. This paper presents the design of a Web-based Intelligent Tutoring System (WITS) based on "Computerized Adaptive Testing" and "Cognitive Diagnostic Assessment". The system is practical and can be implemented incrementally. It is designed for teaching Chinese business writing in Hong Kong to postsecondary students. The proposed system employs self-directed, self-controlled learning ideas and, to some extent, individually packages "assessment" opportunities for individual students. The proposed ITS can be used to identify and gauge the knowledge state and ability levels of each individual student. The estimated knowledge state and ability are useful indicators for teacher and student reference. This paper delineates a prototype. A pilot study will follow in the coming academic year.